Can we trust the model ?
Can we parametrize the model ?
What observed patterns seem to characterize the system and its dynamics, and what variables and processes must be in the model so that these patterns could, in principle, emerge?
When designed to reproduce multiple patterns, models are more likely to be “structurally realistic”
| Parameter | Default | Flat |
|---|---|---|
| gas price | 0.01 | 10 |
| Parameter | Hyper-stability | Hyper-depletion | Negative Relation |
|---|---|---|---|
| \(\epsilon\) | 0.2 | 0.30 | 0.2 |
| \(K\) | 5000 | 8689.205965 | 7500 |
| \(m\) | 0.001 | 0.095023 | 0.085 |
| hold size | 100 | 830 | 800 |
| cell width | 10 | 7.25 | 3.75 |
| gas price | 0.01 | 3.194378 | 0.38 |
| speed | 5.0 | 1.590745 | 0.01 |
| catchability | 0.01 | 0.15 | 0.15 |
A plot of average distance to port per simulation after fixing oil prices and technology. The stepwise shape of the movement only fisher depends on the interaction of fish distribution, oil prices and cell size
| Parameter | Original | No Adaptation |
|---|---|---|
| \(\epsilon\) | 0.2 | 0.27 |
| \(K\) | 5000 | 17004 |
| hold size | 500 | 978 |
| cell width | 1 | 13.27 |
| speed | 5.0 | 3.64 |
| catchability | 0.01 | 0.033 |
| # of fishers | 100 | 143 |
| Parameter | Default | No fishing the line |
|---|---|---|
| \(m\) | 0.001 | 0 |
A sample run where agents are allowed to switch gear and by consequence target species. Fishers tend to respond to variation in relative biomass distribution even without knowing it by following the example of those that are more profitable
| Parameter | Small Difference | Large Difference |
|---|---|---|
| gas price | 0.01 | 10 |
| \(\epsilon\) | 0.2 | 0.8 |
| \(K\) | 5000 | 20000 |
| \(m\) | 0.001 | 0.2 |
| hold size | 100 | 160 |
| cell width | 10 | 20 |
| speed | 5.0 | 14.68 |
| catchability | 0.01 | 0.2 |
| \(\epsilon_{\text{gear}}\) | .2 | .05 |
The dynamics generated by the active non-linear test.
Each line represents the average fuel inefficiency for an indpendent simulation. When facing free gas there is no incentive to improve fuel efficiency and therefore technology on average follows a random walk. The more expensive gas gets the more pronounced the march towards better gear becomes
| Parameter | Adaptation | Random Walk |
|---|---|---|
| gas price | 1 | 1 |
| \(\epsilon\) | 0.2 | 0.48 |
| \(K\) | 5000 | 7242.33 |
| \(m\) | 0.001 | 0.0395 |
| hold size | 100 | 600 |
| cell width | 10 | 20 |
| speed | 5.0 | 0.1 |
| catchability | 0.01 | 0.2 |
| \(\epsilon_{\text{gear}}\) | .2 | .70 |
| \(\delta_{\text{gear}}\) | .05 | .48 |
| max days at sea | 5 | Unlimited |
Each line represents the average fuel inefficiency for an indpendent simulation. Even though the agents are facing high gas prices the biology and the map are structured in such a way as to make movement towards better gear unattractive
| Parameter | Default | No correlation |
|---|---|---|
| gas price | 0.01 | 0 |
The normalized number of tows for each map cell over 5 simulated years for both the scenario with ITQ and TAC policy in place. The dashed line represents the divide between blue and red species at y=24. Any cell on the dashed line and below contains only blue fish (the bycatch) while the cells strictly above the dashed line contains only red fish
| Parameter | Original | No targeting |
|---|---|---|
| \(\epsilon\) | 0.2 | 0.05 |
| \(K\) | 5000 | 17314 |
| hold size | 100 | 10 |
| cell width | 10 | 1 |
| speed | 5.0 | 20 |
| catchability | 0.01 | 0.001 |
| gas price | 0.01 | 10 |
| Parameter | Switch to red gear | Switch to blue gear |
|---|---|---|
| \(\epsilon\) | 0.2 | 0.05 |
| \(K\) | 5000 | 20000 |
| \(m\) | 0.001 | 0.07 |
| hold size | 100 | 10 |
| cell width | 10 | 20 |
| speed | 5.0 | 15 |
| gas price | 0.01 | 0.85 |